Issue In Urban Areas Research Articles

Planning For The Development Of Technical Competence In Land Management (Case Study At The Regional Office Of The National Land Agency, DKI Jakarta Province)

This study aims to design a development plan for technical competencies in land management, specifically within the Regional Office of the National Land Agency (BPN) DKI Jakarta Province. The complexity of land issues in urban areas like Jakarta necessitates the improvement of technical competencies among functional land administrators to ensure effective performance and service delivery. Using a qualitative research approach, data was gathered through interviews, observations, and document analysis. The research highlights the absence of a structured competency development plan for land administrators and suggests the need for tailored training programs. Findings emphasize the importance of digital literacy, land administration skills, legal expertise, and communication skills to meet the demands of modern land management. The study concludes with recommendations for competency development that aligns with organizational goals, proposing a competency framework tailored to the challenges faced in Jakarta.

A place of encounter: Health and social care workers’ perspectives on public gathering spaces for people using drugs

Background: The use of drugs is an escalating concern, with significant implications for the health and daily functionality for individuals. It has proven challenging to provide accessible health and social services. In the context of addressing substance use issues in urban areas, public gathering places for individuals who use drugs play a multifaceted role, serving as sites of belonging, support and potential illicit activity. This qualitative study explores the experiences of healthcare and social workers regarding a public gathering place, referred to as “the Bench”, in a medium-sized Norwegian city. Methods: A qualitative research design consisting of semi-structured focus group interviews and individual interviews with 13 participants representing various support agencies. Results: The analysis resulted in four thematic areas: (1) belonging and a gateway to support and services; (2) balancing user autonomy at the Bench and systems support; (3) the role of a centralised location; and (4) the preventive role of support workers at the Bench. Conclusion: While the Bench fosters a sense of community and provides access to vital services, concerns about illicit activities persist due to its visibility. Nevertheless, its central location facilitates outreach efforts and ensures easy access to support services. The study underscores the preventive role of healthcare and social workers in stabilising the environment and mitigating conflicts. Furthermore, it highlights the importance of central locations for public gathering places, emphasising the proximity to low-threshold services. The Bench represents a crucial venue for establishing relationships and providing assistance to individuals who use drugs, contributing to harm reduction efforts in the community.

A planning framework for intra-city electric bus road transportation systems

Gasoline-based vehicle transportation plays a crucial role in environmental pollution, which eventually leads to serious health issues in urban areas. The scope of large-scale deployment of personalized electric vehicles in the near future can lean toward such issues but can overburden local distribution grids (LDGs), and the entities are producing green energy. In this context, an electric bus road transportation system (EBRTS) can be seen as an effective and promising way, although it is capital-intensive. EBRTs can be successfully deployed by developing a well-tailored planning model that encompasses amicable solutions while considering the conflicting interests of electric utilities and investors/transporters.This paper proposes a planning model for intra-city EBRTS, especially for metropolitan cities, to extract tangible benefits in favour of electric utilities and private players. The proposed framework envisages a bus fleet charging model and financial model within the spatial, technical, and financial constraints yet preserves the interests of electric utilities and investors by providing tentative solutions with all information necessary from the investor’s perspective. The methodology is free from optimization as the realistic constraints inherently employ search space reduction. The simulation results on a real public transportation system reveal the proposed methodology’s simplicity, rationality, applicability, and flexibility.

Hydraulic Property Estimation of Green Roof Substrates from Soil Moisture Time Series

The adoption of green roofs is an effective practice for mitigating environmental issues in urban areas caused by extreme weather conditions. However, certain design aspects of green roofs, such as the characterization of the physical properties of their substrates, need a better understanding. This study proposes a simple method for estimating two hydraulic properties of green roof substrates based on the evolution of moisture during drying periods, or drydowns, where evaporative processes dominate: the weighted-mean diffusivity and the saturated hydraulic conductivity. Soil moisture was monitored using 12 in situ sensors from 2015 to 2020 in a study involving six different green roof plots composed of various mixtures of demolition-recycled aggregates and organic substrates. A universal parameterization for determining water diffusivity in soils was applied to estimate the weighted-mean hydraulic diffusivity. As a by-product, the saturated hydraulic conductivity was estimated from the evaluated diffusivity and the measured water retention data. The median values obtained for and range from 14.5 to 29.9 cm2d−1 and from 22 to 361 cmd−1, respectively. These values fall within the ranges reported by other research groups using direct measurement methods and supports the validity of Brutsaert’s model for green roof substrates. Furthermore, an increase in and a decrease in were observed as the percentage of recycled aggregates in the substrates increased, which could be considered for design purposes.

Heat stress risk at an intra-urban level: A case study of Delhi, India

Cities throughout the globe are expanding due to rapid urbanization. The risk associated with heat on residents is increasing and thus requires interventions at an intraurban level. This study aims to determine the spatial distribution of the heat stress risk index (HSRI) in an urban area of Delhi (India). This study illustrates a novel technique using meteorological variables simulated from a numerical weather prediction urban canopy model (WRF-UCM) to generate the Universal Thermal Climate Index (UTCI) in the city of Delhi at a resolution of 333 m. The estimated UTCI is then optimally blended with the socioeconomic vulnerability and exposure indices generated through the identification of suitable parameters via principal component analysis (PCA). The analysis based on the high-resolution UTCI risk index showed that within the existing framework, 88 % of the city falls under a heat stress risk above the “Moderate to Highest” category of stress values, which explicitly affects the population and requires urgent interventions for the development of a resilient and sustainable city. The study also revealed that the areas with the highest UTCIs may not correspond to the zones related to the highest heat stress risk. This suggests that the HSRI rather than the UTCI alone should be the optimal indicator for consideration by stakeholders when developing policies to mitigate heat stress-related issues in urban areas under changing climate.

Modeling Pedestrian Near-Crash Events at a Rectangular Rapid Flashing Beacon-Controlled Intersection Using Video Analytics and Long Short-Term Memory Neural Network

Pedestrian safety is a long-standing issue in urban areas, where pedestrian near-crash events are more frequent than in suburban or rural areas. To address the pedestrian safety problem, a proactive approach was explored to assess and predict the severity of these events, which are valuable indicators of potential crashes. Object detection and tracking techniques were used to establish the temporal relationship of pedestrian near-crash events involving vehicles at an intersection controlled with rectangular rapid flashing beacons. A long short-term memory (LSTM) neural network model is proposed to warn a driver 2 s before the vehicle reaches the conflict zone. However, this scenario can be considered optimistic, as the 2 s interval represents an ideal driver’s reaction time, which is more likely to happen in a connected and automated vehicle environment where vehicles receive real-time information about their surroundings and perform some basic tasks such as braking without waiting for the driver reaction. The results demonstrate the effectiveness of the proposed LSTM neural network model, with an area under the curve value of 78.5% on the training data and an overall recall of 71.1% on the test data. The practical significance of this model is its potential to provide timely information about near-crash events, thereby enhancing pedestrian safety at critical points such as intersections.

A framework to include socio-demographic characteristics in potential job accessibility levels in low-car and car-free development areas in the Netherlands

Car-free development has become popular in recent years due to concerns regarding transport-related health issues in urban areas as well as a growing trend toward sustainability and environmentally friendly living. Although car-free development is regarded as progress to promote active transport modes and healthier cities, the accessibility impacts for its residents remain unclear. To address this knowledge gap, this paper proposes a job accessibility assessment framework that integrates individual and household socio-demographic characteristics into a job accessibility assessment, making it possible to account for commuting preferences of different population groups in accessibility analyses. For this purpose, a stated choice survey was conducted in existing low-car areas in the Netherlands to determine transport use and perception of public transport trip characteristics. Then, the influence of socio-demographic characteristics on trip perceptions was analyzed using a Latent Class Logit (LCL) regression model and Monte Carlo simulations. Finally, a multi-modal transport network combining walking and public transport trips was used to assess potential job accessibility levels of different population groups in a car-free development area. The proposed framework was implemented in a case study in the province of Utrecht (the Netherlands). Results show notable differences between the job accessibility levels within different population groups, reflecting distinct perceptions toward commuting trip characteristics based on socio-demographic characteristics and demonstrating the suitability of the applied approach to assess accessibility levels in car-free development areas. Compared to the sample average distribution, more than 15% lower accessibility levels were observed for starters (age 18-35) in some urban areas, indicating the aversion to longer and more expensive commuting trips. Contrarily, increased accessibility levels for families (>2 persons in household) were observed, demonstrating the acceptance to experience longer commuting travel times and additional costs. No differences were observed between accessibility levels of the sample average and senior adults (age >50).

LOW-RISE HIGH-DENSITY HOUSING – POSSIBILITIES OF IMPLEMENTATION IN LOCAL CONTEXT, CASE OF NIŠ, SERBIA

<p class="ABSTRACT">Low-rise, high-density housing (further LRHD housing) represents an alternative model for solving contemporary housing issues in urban areas. However this specific typological form is not recognized in local urban planning and legislative frameworks. The aim of this research is to explore the possibilities for development of LRHD housing within local frameworks through the assessment of urban parameters potentially achievable through the application of the pilot Mix-Mesh concept for LRHD housing and their comparative analysis with values defined by local planning regulations.</p>

Green architecture: Conceptualizing vertical greenery in urban design

This executive summary introduces the concept paper on Green Architecture, focusing specifically on the integration of vertical greenery in urban design. Green architecture, characterized by sustainable design principles and environmental consciousness, aims to enhance urban environments by incorporating vegetation into built structures. Vertical greenery, a key component of green architecture, involves the strategic placement of vegetation on vertical surfaces such as walls, facades, and rooftops. This concept paper explores the potential of vertical greenery to mitigate environmental issues in urban areas, improve air quality, reduce the urban heat island effect, and enhance biodiversity. The paper proposes a conceptual framework for conceptualizing vertical greenery in urban design, emphasizing the importance of integrating natural elements into the built environment. It discusses various strategies for implementing vertical greenery, including the selection of suitable plant species, design considerations for irrigation and structural stability, and the incorporation of greenery into urban planning processes. Moreover, the concept paper highlights the social and economic benefits of vertical greenery, such as improved health and well-being for residents, increased property values, and enhanced aesthetics of urban spaces. It also emphasizes the role of stakeholder engagement, interdisciplinary collaboration, and ongoing monitoring and evaluation in the successful implementation of vertical greenery projects. In conclusion, this executive summary outlines the significance of incorporating vertical greenery into urban design practices as a means to promote sustainability, resilience, and livability in cities. By embracing the principles of green architecture and integrating vertical greenery into urban landscapes, cities can create healthier, more vibrant, and environmentally sustainable communities for current and future generations. Keywords: Urban, Design, Green, Architecture, Vertical.

Guiding to available parking spots with AR device

Parking congestion has become a pressing issue in urban areas, leading to increased traffic congestion and environmental pollution. This paper presents a comprehensive study on intelligent parking systems aimed at addressing these challenges. The study targets urban drivers, transport authorities and citizens who are affected by parking difficulties and traffic congestion. Intelligent Parking System is a technology-driven solution that aims to optimise parking space utilisation and reduce traffic congestion. It efficiently guides drivers to available parking spaces through real-time data collection and analysis. The study was conducted in Unity3D environment over a period of 2 weeks and covered the phases of system design, development, testing and implementation. The main motivation for this research was to mitigate the negative effects of parking congestion. Intelligent parking systems have the potential to increase traffic efficiency, reduce air pollution and improve the overall quality of life in cities. Server and Unity models were used in the study. Real-time sensors collect parking occupancy data, which is processed to provide real-time parking availability information to drivers via the server. In conclusion, this paper presents an intelligent parking system that can solve the challenges of parking congestion. By utilising server technology and data-driven insights, the project aims to improve the way cities manage parking and contribute to more sustainable urban mobility.

Barriers to municipal solid waste management policy implementation. A case study in KwaZulu-Natal, South Africa

ABSTRACT While literature extensively examines waste management issues in urban areas, limited attention has been given to rural developing waste contexts. This paper aims to understand the policy/implementation nexus between national and local government within the rural waste management context in two rural municipalities in KwaZulu-Natal, South Africa. The research utilizes a directed deductive content analysis applying a framework proposed by Pollans. Originally designed for urban contexts, this framework has proven valuable for comprehending solid waste management policy implementation challenges in rural settings. This paper proposes an adjustment to this framework, differentiating the disposal mode of governing into government-based and self-reliant-based approaches. The authors found a significant implementation gap in both municipalities, characterized by a predominant, incremental disposal-oriented governing mode. This contrasts with the visionary and aspirational modes of governing promoted by the national government, focusing on diversion and eco-efficient waste strategies. These divergent modes of governing influence current waste management practices, especially in rural municipalities. We recommend strategies towards narrowing the implementation gap by formulating policies tailored to local development needs. Finally, the research sheds light on the challenges and disparities in rural waste management policy implementation and provides insights into how rural areas can transition towards sustainable waste management practices.

Determining Digitalization Issues (ICT Adoption, Digital Literacy, and the Digital Divide) in Rural Areas by Using Sample Surveys: The Case of Armenia

Digital technologies have penetrated all spheres of human life, becoming an integral element of sustainable development, and rural areas and agriculture are no exception. However, the processes of digital transformation possess certain challenges. Among them are ICT penetration, digital literacy of society, and the digital divide. This article aims to evaluate the digital penetration and the digital divide in rural areas of Armenia and identify and propose directions for improvement. For that purpose, a sample survey was conducted among rural households. The questionnaires included questions aimed at assessing digital literacy, as well as the level of ICT penetration and use. In addition, the Digital Devices and Technologies Usage Index (DTUI) was composed and calculated. The comparison of DTUI values revealed that being distant from the capital Yerevan can negatively impact ICT usage and digital penetration. It was revealed that households with higher incomes tend to use more ICT, which can indicate a possible positive relationship between DTUI and can be further studied by integrating econometric regression analysis. To facilitate and accelerate the processes of digital penetration and ICT use in rural areas of Armenia, relevant proposals were presented in the scope of the article. The results of this article can be useful for policymakers and the results part can be relevant for wider audiences. In particular, the recommendations presented in the article can be used by the RA Government as practical state support measures aimed at the promotion of digitalization in rural areas. Further research can include the digitalization issues in urban areas and provide insights into the digital divide between urban and rural areas.

Efficient Road Traffic Video Congestion Classification Based on the Multi-Head Self-Attention Vision Transformer Model

Abstract Due to rapid population growth, traffic congestion has become one of the major issues in urban areas. The utilization of technology may help to address this issue. This paper proposes a new Multi-head Self-attention Vision Transformer (MSViT) based macroscopic approach, for road traffic congestion classification. To evaluate this approach, we use the UCSD (University of California San Diego) dataset that includes different weather conditions (clear, overcast and rainy) and different traffic scenarios (light, medium and heavy). The classification accuracy reached a high level of 99.76% with this dataset and 99.37% when night-mode frames are added to it. The proposed MSViT based method outperforms the state-of-the-art macroscopic and microscopic methods that have been evaluated using the same UCSD dataset, which makes it an efficient solution for traffic congestion prediction.

The proposed model for analyzing off-street parking Dynamics: A case study of Taipei City

To reduce traffic congestion, air pollution, and lost revenue due to wasted driving around looking for parking spaces, effective parking management has become a crucial issue in urban areas. Previous studies have shown that parking demand is related to the location of parking spaces/lots, parking fees, time spent looking for spaces, and various driver and environmental characteristics. However, there have been more studies of on-street rather than off-street parking. Also, the spatio-temporal variance between variables and turnover rate (such as the hours of operation for various types of Points of Interest (POIs) as well as the causes of bias estimators has been largely overlooked.To solve the above problems, the Geographical and Temporal Weighted Regression (GTWR) model was utilized in this study to predict the hourly parking turnover rate in off-street parking lots. The flexible coefficient setting of this model can be used to capture the spatial and temporal variance. In addition to this model, the Geographically Weighted Regression (GWR) and the Ordinary Least Squares (OLS) models were used as a basis for comparison. The study included 346 public off-street parking lots in Taipei and 10 types of nearby POIs. The study period was for 24 h on August 31, 2021. Due to the dissimilar trend of the turnover rate, the researchers separated all parking lots into three groups for regression analysis: those that experience a daytime decrease, remain stable, and those with an increase during the day.Our results show the following: (1) For the types of parking lots that experienced increases and decreases, the GTWR model performed best for the prediction of hourly turnover rate, while all models performed similarly for the prediction of the stable type parking lot. (2) With regard to related factors (the type 1 parking lot for example), parking lots in areas with more traditional markets, MRT stations, and with fewer schools, supermarkets, hotel bus stops, and lower parking fees tended to have higher turnover rates. (3) Incorporating a more precise POI dataset (the number and types of POIs as well as their business hours) and applying a suitable spatial temporal model improved the parking demand model’s performance. However, the GTWR model’s limitations may hamper its performance, especially with regard to analysis of the time-stable parking lots or variables. Future studies might include other datasets, such as nearby private parking lots or holiday data to improve the model fit.

Cool Concrete Incorporating Carbonated Periwinkle Shell: A Sustainable Solution for Mitigating Urban Heat Island Effects.

The urban heat island effect has become a critical issue in urban areas, intensifying heat-related problems and increasing energy consumption. A sustainable cement formulation that combines ordinary Portland cement (OPC) with a carbonated aggregate derived from Periwinkle shell powder for the development of an efficient cool material is presented. Through a carbonation process, the aggregate undergoes a transformation, capturing carbon dioxide (CO2) and converting it into calcite. The resulting cement mixture exhibits high solar reflective properties, making it a potential candidate for cool pavement and roof applications. In this study, the raw materials, including the Periwinkle shell powder, were characterized, and the carbonation process was evaluated to quantify the CO2 capture efficiency. Additionally, a real test of the efficiency of this new cement on a roof demonstrated that the material achieved a significant cooling effect, being 6 °C cooler than that with standard OPC at the peak of solar radiation.

Environmental Sustainability Implications and Economic Prosperity of Integrated Renewable Solutions in Urban Development

The increasing urbanization and growth of cities worldwide have led to a significant increase in energy demand. As a transition to a low carbon environment occurs, the role of renewable and sustainable energy systems in urban areas is benefiting industry and the environment alike. From this perspective, the Sustainable Development Goals (SDGs) have a lot to offer to the energy industry, particularly the integration of renewable and sustainable energy systems for environmental protection in cities. This study presents a comprehensive view that integrates technological, economic, political, and social challenges confronted with the effective implementation of renewable and sustainable energy in urban cities and proposes a solution agenda to overcome these hurdles with the aid of the SDGs. The weights for the challenges of adopting renewable and sustainable energy systems were determined using the Fuzzy Best-Worst Method. The SDGs were then ranked using the fuzzy TOPSIS technique to overcome predetermined challenges. The originality of this study lies in finding solutions to the determined challenges by adopting SDGs, emphasizing the need for integrated solutions that address energy-related concerns, and highlighting the role and importance of SDGs in environmental protection. The study highlights the importance of SDGs in promoting renewable energy integration in urban areas, with SDG 11 being the most crucial to mitigate harmful environmental occurrences related to energy-related issues in urban areas, followed by SDG 7 and SDG 13.

Policy Triangle Analysis of Stunting Issues in Urban Areas: A Case Study of Yogyakarta City

Stunting reduction is one of Indonesia’s major projects. While one-size-fits-all regulations were no longer promoted, understanding the characteristics of each region imposed a strong policy foundation. Many studies had been conducted in rural areas, but the analysis of urban areas was scarce. A study was conducted in Yogyakarta City to understand the characteristics of stunting intervention, despite the high human development index, education level, and access to health facilities. This made it important to examine the characteristics of stunting reduction efforts, based on the analysis of the contents, contexts, processes, and actors involved, in Yogyakarta City, to help with its ambition for zero stunting. A desk review and focus group discussion were conducted involving four local government staff, consisting of the Regional Planning and Development Agency, Health Office, and Office of Women's Empowerment, Child Protection, and Population Control and Family Planning, which were elaborated with literature following the policy triangle framework. A total of 13 open-access official documents and dashboards were obtained for analysis. Decrees from the local government showed a strong commitment to ending malnutrition. While most intervention packages were similar to those across Indonesia, targeted interventions for specific subjects were needed to support people who were unable to be covered by general services. Furthermore, Yogyakarta City has smaller open spaces than other districts in the province, a contradictory low nutrition awareness despite high school participation, and other factors were cross-linked with its culture in the community, implementer, to the authority levels. Stunting reduction programs were multisectoral, involving not only government offices but also non-government, mass media, community, private sectors, and academia. This study is expected to provide lessons learned for decision-makers, private sectors, academia, and public health practitioners to implement good collaboration in stunting reduction efforts.

TEHRAN AIR POLLUTION MODELING USING LONG-SHORT TERM MEMORY ALGORITHM: AN UNCERTAINTY ANALYSIS

Abstract. Air pollution is a major environmental issue in urban areas, and accurate forecasting of particles 10 μm or smaller (PM10) level is essential for smart public health policies and environmental management in Tehran, Iran. In this study, we evaluated the performance and uncertainty of long short-term memory (LSTM) model, along with two spatial interpolation methods including ordinary kriging (OK) and inverse distance weighting (IDW) for mapping the forecasted daily air pollution in Tehran. We used root mean square error (RMSE) and mean square error (MSE) to evaluate the prediction power of the LSTM model. In addition, prediction intervals (PIs), and Mean and standard deviation (STD) were employed to assess the uncertainty of the process. For this research, the air pollution data in 19 Tehran air pollution monitoring stations and temperature, humidity, wind speed and direction as influential factors were taken into account. The results showed that the OK had better RMSE and STD in the test (32.48 ± 9.8 μg/m3) and predicted data (56.6 ± 13.3 μg/m3) compared with those of the IDW in the test (47.7 ± 22.43 μg/m3) and predicted set (62.18 ± 26.1 μg/m3). However, in PIs, IDW ([0, 0.7] μg/m3) compared with the OK ([0, 0.5] μg/m3) had better performance. The LSTM model achieved in the predicted values an RMSE of 8.6 μg/m3 and a standard deviation of 9.8 μg/m3 and PIs between [2.7 ± 4.8, 14.9 ± 15] μg/m3.

Automated Vacancy Detection in a Parking-lOT using Image Processing and Remote Access to Real-Time State

Abstract: There has been a sudden increase in the number of vehicles in recent years. Availability of parking spaces is now become a critical issue in urban areas. Finding unoccupied space for parking vehicles has now become a challenge for drivers as it results in time wastage, loss of fuel, and increased traffic congestion. To reduce such problems, an intelligent system is required that can detect vacant parking spots in a specific parking lot. In a research paper, we present an automated vacancy detection system that uses image processing to detect the available parking spots in a parking lot. A proposed system consists of a camera that monitors the real-time state of the parking lot, an image processing unit, and a display outside the parking lot for users, showing the availability of parking spots. A system uses a vehicle detection algorithm to recognize the presence of vehicles in a parking space. The algorithm includes image binarization, dilation of an image, and edge detection. As the system identifies the available parking spaces accurately, the user display gets updated.

Comparison of the ozone formation mechanisms and VOCs apportionment in different ozone pollution episodes in urban Beijing in 2019 and 2020: Insights for ozone pollution control strategies

Ground-level ozone (O3) pollution has been a tough issue in urban areas of China in the past decade. Clarifying the formation mechanisms of O3 and the sources of its precursors is necessary for the effective prevention of O3 pollution. In this study, a comparative analysis of O3 formation mechanisms and VOCs apportionment for five O3 pollution episodes was carried out at two urban sites (CRAES and CGZ) in Beijing in 2019 and 2020 by applying an observation-based modeling approach in order to obtain insights into O3 pollution control strategies. Results indicated that O3 pollution levels were generally more severe in 2019 than in 2020 during the observation periods. O3 formation at the two sites was both VOCs-limited on O3 polluted days and non-O3 polluted days. Stronger atmospheric oxidation capacity and ROx radicals cycling processes were found on O3 polluted days which could accelerate the local production of O3, and local photochemical production dominated the observed O3 concentrations at the two sites even on non-O3 polluted days. Emission reduction of VOCs should be a priority for mitigating O3 pollution, and alkenes and biogenic VOCs was the priority species at the CRAES and CGZ sites, respectively. Additionally, the reduction of oxygenated VOCs should also be important for the ozone control. Gasoline exhaust at the CRAES site, and solvent utilization and fuel evaporation at the CGZ site were main anthropogenic sources of VOCs. Therefore, local control measures should be further strengthened and differentiated control strategies of VOCs in the aspects of area, time, sources and species should be adopted in urban Beijing in the future. Overall, the findings of this study could provide a scientific understanding of the causes of O3 pollution and significant guidelines for formulating O3 control strategies from the perspective of different ozone pollution episodes in urban Beijing.